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    Playwright Fetch

    A fetch mcp server

    1 stars
    Python
    Updated Oct 3, 2025

    Table of Contents

    • Author
    • Key Features
    • Available Tools
    • Prompts
    • Requirements
    • Installation
    • 1. Install with uv (recommended)
    • 2. Using Docker
    • Configuration
    • Configure for Claude.app
    • Configure for VS Code
    • Command Line Options
    • Example Usage
    • Debugging
    • Differences from Standard Fetch Server
    • License

    Table of Contents

    • Author
    • Key Features
    • Available Tools
    • Prompts
    • Requirements
    • Installation
    • 1. Install with uv (recommended)
    • 2. Using Docker
    • Configuration
    • Configure for Claude.app
    • Configure for VS Code
    • Command Line Options
    • Example Usage
    • Debugging
    • Differences from Standard Fetch Server
    • License

    Documentation

    Playwright Fetch MCP Server

    GitHub release (latest by date)

    CI

    codecov

    License: MIT

    Python Version

    Playwright

    MCP

    Code style: black

    A Model Context Protocol server that provides web content fetching capabilities using Playwright for browser automation. This server enables LLMs to retrieve and process JavaScript-rendered content from web pages, converting HTML to markdown for easier consumption.

    Author

    Created by Wyatt Roersma with assistance from Claude Code.

    Key Features

    • Browser Automation: Uses Playwright to render web pages with full JavaScript support
    • Content Extraction: Automatically identifies and extracts main content areas from web pages
    • Markdown Conversion: Converts HTML to clean, readable markdown
    • Pagination Support: Handles large content through pagination
    • Robots.txt Compliance: Respects robots.txt directives for autonomous fetching
    • Proxy Support: Allows routing requests through a proxy server
    • Docker Ready: Available as pre-built Docker images via Docker Hub and GitHub Container Registry

    Available Tools

    • playwright-fetch - Fetches a URL using Playwright browser automation and extracts its contents as markdown.
    • url (string, required): URL to fetch
    • max_length (integer, optional): Maximum number of characters to return (default: 5000)
    • start_index (integer, optional): Start content from this character index (default: 0)
    • raw (boolean, optional): Get raw content without markdown conversion (default: false)
    • wait_for_js (boolean, optional): Wait for JavaScript to execute (default: true)

    Prompts

    • playwright-fetch
    • Fetch a URL using Playwright and extract its contents as markdown
    • Arguments:
    • url (string, required): URL to fetch

    Requirements

    • Python 3.13.2 or newer
    • uv package manager
    • Playwright browsers installed

    Installation

    1. Install with uv (recommended)

    bash
    uv pip install git+https://github.com/ThreatFlux/playwright-fetch.git
    # Install Playwright browsers
    uv pip exec playwright install

    Alternatively, clone the repository and install:

    bash
    git clone https://github.com/ThreatFlux/playwright-fetch.git
    cd playwright-fetch
    uv pip install -e .
    # Install Playwright browsers
    uv pip exec playwright install

    2. Using Docker

    You can use our pre-built Docker images from Docker Hub or GitHub Container Registry:

    bash
    # From Docker Hub
    docker pull threatflux/playwright-fetch:latest
    
    # From GitHub Container Registry
    docker pull ghcr.io/threatflux/playwright-fetch:latest

    Or build it yourself:

    bash
    docker build -t threatflux/playwright-fetch .

    Configuration

    Configure for Claude.app

    Add to your Claude settings:

    Using uvx

    json
    "mcpServers": {
      "playwright-fetch": {
        "command": "uvx",
        "args": ["mcp-server-playwright-fetch"]
      }
    }

    Using docker

    json
    "mcpServers": {
      "playwright-fetch": {
        "command": "docker",
        "args": ["run", "-i", "--rm", "threatflux/playwright-fetch"]
      }
    }

    Configure for VS Code

    For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code.

    Using uvx

    json
    {
      "mcp": {
        "servers": {
          "playwright-fetch": {
            "command": "uvx",
            "args": ["mcp-server-playwright-fetch"]
          }
        }
      }
    }

    Using Docker

    json
    {
      "mcp": {
        "servers": {
          "playwright-fetch": {
            "command": "docker",
            "args": ["run", "-i", "--rm", "threatflux/playwright-fetch"]
          }
        }
      }
    }

    Command Line Options

    The server supports these command-line options:

    • --user-agent: Custom User-Agent string
    • --ignore-robots-txt: Ignore robots.txt restrictions
    • --proxy-url: Proxy URL to use for requests
    • --headless: Run browser in headless mode (default: True)
    • --wait-until: When to consider navigation succeeded (choices: "load", "domcontentloaded", "networkidle", "commit", default: "networkidle")

    Example Usage

    bash
    # Run with default settings
    uv run mcp-server-playwright-fetch
    
    # Run with a custom user agent and proxy
    uv run mcp-server-playwright-fetch --user-agent="MyCustomAgent/1.0" --proxy-url="http://myproxy:8080"
    
    # Run with visible browser for debugging
    uv run mcp-server-playwright-fetch --headless=false

    Debugging

    You can use the MCP inspector to debug the server:

    bash
    npx @modelcontextprotocol/inspector uvx mcp-server-playwright-fetch

    Differences from Standard Fetch Server

    This implementation differs from the standard fetch MCP server in these ways:

    1. Browser Automation: Uses Playwright to render JavaScript-heavy pages

    2. Content Extraction: Attempts to extract main content from common page structures

    3. Wait Options: Configurable page loading strategy (wait for load, DOM content, network idle)

    4. Visible Browser Option: Can run with a visible browser for debugging

    License

    This project is licensed under the MIT License. See the LICENSE file for details.

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